作　　者： ; ; ;

机构地区： 山东科技大学

出　　处： 《微电子学与计算机》 2013年第3期80-84,共5页

摘　　要： 复合数据服务是由具有层次结构的多个原子数据服务组合而成,是实现跨域数据集成的一种手段.当底层数据服务发生数据更新时,数据更新如何自下而上经过多个中间复合数据服务传播到顶层,并在这个传播的过程中保障顶层复合数据服务的更新效率就成为一个挑战问题.针对这一问题,提出一种基于缓存的复合数据服务更新优化方法.该方法根据缓存点成本收益模型找出复合数据服务的最佳缓存点,并且通过B树索引查找缓存点,重用缓存数据,避免重复的更新计算.实验表明,该方法提高了复合数据服务的更新效率. A composite data service is composed of a number of basic data services with hierarchical structure. It is one of the important approaches for cross--domain data integration. Once a primitive data service is updated, it becomes a question of how to propagate the update bottom--up to the top level via several intermediate composite data services, and to ensure the update efficiency of the data view. This paper intends to present a cache--based optimization method for the composite data services, which is based on a cost--benefit model of cache points to find the best cache point of the composite data services. In addition, when the data services update, we can find the cache point quickly and efficiently to reuse the cached data through the B--tree index, that avoid repeat of the updated calculation. Experiments show that our approach can effectively improve the update efficiency of the composite data services.

关 键 词： 数据服务 服务聚合 服务优化 缓存

领　　域： [自动化与计算机技术] [自动化与计算机技术]